tests/TfLiteMobilenetQuantized-Armnn/TfLiteMobilenetQuantized-Armnn.cpp

   1 //
   2 // Copyright © 2017 Arm Ltd. All rights reserved.
   3 // See LICENSE file in the project root for full license information.
   4 //
   5 #include "../InferenceTest.hpp"
   6 #include "../ImagePreprocessor.hpp"
   7 #include "armnnTfLiteParser/ITfLiteParser.hpp"
   8
   9 using namespace armnnTfLiteParser;
  10
  11 int main(int argc, char* argv[])
  12 {
  13     int retVal = EXIT_FAILURE;
  14     try
  15     {
  16         // Coverity fix: The following code may throw an exception of type std::length_error.
  17         std::vector<ImageSet> imageSet =
  18         {
  19             {"Dog.jpg", 209},
  20             // top five predictions in tensorflow:
  21             // -----------------------------------
  22             // 209:Labrador retriever 0.949995
  23             // 160:Rhodesian ridgeback 0.0270182
  24             // 208:golden retriever 0.0192866
  25             // 853:tennis ball 0.000470382
  26             // 239:Greater Swiss Mountain dog 0.000464451
  27             {"Cat.jpg", 283},
  28             // top five predictions in tensorflow:
  29             // -----------------------------------
  30             // 283:tiger cat 0.579016
  31             // 286:Egyptian cat 0.319676
  32             // 282:tabby, tabby cat 0.0873346
  33             // 288:lynx, catamount 0.011163
  34             // 289:leopard, Panthera pardus 0.000856755
  35             {"shark.jpg", 3},
  36             // top five predictions in tensorflow:
  37             // -----------------------------------
  38             // 3:great white shark, white shark, ... 0.996926
  39             // 4:tiger shark, Galeocerdo cuvieri 0.00270528
  40             // 149:killer whale, killer, orca, ... 0.000121848
  41             // 395:sturgeon 7.78977e-05
  42             // 5:hammerhead, hammerhead shark 6.44127e-055
  43         };
  44
  45         armnn::TensorShape inputTensorShape({ 1, 224, 224, 3  });
  46
  47         using DataType = uint8_t;
  48         using DatabaseType = ImagePreprocessor<DataType>;
  49         using ParserType = armnnTfLiteParser::ITfLiteParser;
  50         using ModelType = InferenceModel<ParserType, DataType>;
  51
  52         // Coverity fix: ClassifierInferenceTestMain() may throw uncaught exceptions.
  53         retVal = armnn::test::ClassifierInferenceTestMain<DatabaseType,
  54                                                           ParserType>(
  55                      argc, argv,
  56                      "mobilenet_v1_1.0_224_quant.tflite", // model name
  57                      true,                                // model is binary
  58                      "input",                             // input tensor name
  59                      "MobilenetV1/Predictions/Reshape_1", // output tensor name
  60                      { 0, 1, 2 },                         // test images to test with as above
  61                      [&imageSet](const char* dataDir, const ModelType & model) {
  62                          // we need to get the input quantization parameters from
  63                          // the parsed model
  64                          auto inputBinding = model.GetInputBindingInfo();
  65                          return DatabaseType(
  66                              dataDir,
  67                              224,
  68                              224,
  69                              imageSet,
  70                              inputBinding.second.GetQuantizationScale(),
  71                              inputBinding.second.GetQuantizationOffset());
  72                      },
  73                      &inputTensorShape);
  74     }
  75     catch (const std::exception& e)
  76     {
  77         // Coverity fix: BOOST_LOG_TRIVIAL (typically used to report errors) may throw an
  78         // exception of type std::length_error.
  79         // Using stderr instead in this context as there is no point in nesting try-catch blocks here.
  80         std::cerr << "WARNING: " << *argv << ": An error has occurred when running "
  81                      "the classifier inference tests: " << e.what() << std::endl;
  82     }
  83     return retVal;
  84 }